System and method for generating baseline data for automated management of cardiovascular pressure

ABSTRACT

A system and method for generating baseline data for automated management of cardiovascular pressure is disclosed. Collected device measures are accumulated to record raw physiometry for a patient, wherein the patient is regularly monitored by an implantable medical device, beginning with an initial observation period. Derived device measures are generated to provide derivative physiometry determined at least in part from the collected device measures. A patient status indicator is determined by analyzing the collected and derived device measures to diagnose a pathophysiology indicative of an absence, onset, progression, regression, and status quo in cardiovascular pressure, wherein the collected and derived device measures and the patient status indicator originating from the initial observation period include baseline data.

CROSS-REFERENCE TO RELATED APPLICATION

This patent application is a continuation of U.S. patent applicationSer. No. 11/635,205, filed Dec. 6, 2006, pending, which is acontinuation of U.S. Pat. No. 7,248,916, issued Jul. 24, 2007, which isa continuation of U.S. Pat. No. 6,221,011, issued Apr. 24, 2001, thedisclosures of which are incorporated by reference, and the priorityfiling dates of which are claimed.

FIELD OF THE INVENTION

The present invention relates in general to automated data collectionand analysis, and, in particular, to a system and method for determininga reference baseline of individual patient status for use in anautomated collection and analysis patient care system.

BACKGROUND OF THE INVENTION

Implantable pulse generators (IPGs) are medical devices commonly used totreat irregular heartbeats, known as arrhythmias. There are three basictypes. Cardiac pacemakers are used to manage bradycardia, an abnormallyslow or irregular heartbeat. Bradycardia can cause symptoms such asfatigue, dizziness, and fainting. Implantable cardioverterdefibrillators (ICDs) are used to treat tachycardia, heart rhythms thatare abnormally fast and life threatening. Tachycardia can result insudden cardiac death (SCD). Implantable cardiovascular monitors andtherapeutic devices are used to monitor and treat structural problems ofthe heart, such as congestive heart failure, as well as rhythm problems.

Pacemakers and ICDs are equipped with an on-board, volatile memory inwhich telemetered signals can be stored for later retrieval andanalysis. In addition, a growing class of cardiac medical devices,including implantable heart failure monitors, implantable eventmonitors, cardiovascular monitors, and therapy devices, are being usedto provide similar stored device information. These devices are able tostore more than thirty minutes of per heartbeat data. Typically, thetelemetered signals can provide patient device information recorded on aper heartbeat, binned average basis, or derived basis from, for example,atrial electrical activity, ventricular electrical activity, minuteventilation, patient activity score, cardiac output score, mixed venousoxygen score, cardiovascular pressure measures, time of day, and anyinterventions and the relative success of such interventions.Telemetered signals are also stored in a broader class of monitors andtherapeutic devices for other areas of medicine, including metabolism,endocrinology, hematology, neurology, muscular disorders,gastroenterology, urology, ophthalmology, otolaryngology, orthopedics,and similar medical subspecialties.

These telemetered signals can be remotely collected and analyzed usingan automated patient care system. One such system is described in arelated, commonly-owned U.S. Pat. No. 6,312,378, issued Nov. 6, 2001.The telemetered signals are recorded by an implantable medical device,such as an IPG or monitor, and periodically retrieved using aninterrogator, programmer, telemetered signals transceiver, or similardevice, for subsequent download. The downloaded telemetered signals arereceived by a network server on a regular, e.g., daily, basis as sets ofcollected measures which are stored along with other patient records ina database. The information is analyzed in an automated fashion andfeedback, which includes a patient status indicator, is provided to thepatient.

While such a system can serve as a valuable tool in automated, remotepatient care, the accuracy of the patient care, particularly during thefirst few weeks of care, and the quality of the feedback provided to thepatient would benefit from being normalized to a reference baseline ofpatient wellness. In particular, a starting point needs to beestablished for each individual patient for use in any such system inwhich medical device information, such as telemetered signals fromimplantable medical devices, is continuously monitored, collected, andanalyzed. The starting point could serve as a reference baselineindicating overall patient status and wellness from the outset of remotepatient care.

In addition, automated remote patient care poses a further challengevis-à-vis evaluating quality of life issues. Unlike in a traditionalclinical setting, physicians participating in providing remote patientcare are not able to interact with their patients in person.Consequently, quality of life measures, such as how the patientsubjectively looks and feels, whether the patient has shortness ofbreath, can work, can sleep, is depressed, is sexually active, canperform activities of daily life, and so on, cannot be implicitlygathered and evaluated.

Reference baseline health assessments are widely used in conventionalpatient health care monitoring services. Typically, a patient's vitalsigns, consisting of heart rate, blood pressure, weight, and blood sugarlevel, are measured both at the outset of care and periodicallythroughout the period of service. However, these measures are limited intheir usefulness and do not provide the scope of detailed medicalinformation made available through implantable medical devices.Moreover, such measures are generally obtained through manual means anddo not ordinarily directly tie into quality of life assessments.Further, a significant amount of time generally passes between thecollection of sets of these measures.

Thus, there is a need for an approach to determining a meaningfulreference baseline of individual patient status for use in a system andmethod for providing automated, remote patient care through thecontinuous monitoring and analysis of patient information retrieved froman implantable medical device. Preferably, such an approach wouldestablish the reference baseline through initially received measures orafter a reasonable period of observation. The reference baseline couldbe tied to the completion of a set of prescribed physical stressors.Periodic reassessments should be obtainable as necessary. Moreover, thereference baseline should preferably be capable of correlation toquality of life assessments.

There is a further need for an approach to monitoring patient wellnessbased on a reference baseline for use in an automated patient caresystem. Preferably, such an approach would dynamically determine whetherthe patient is trending into an area of potential medical concern.

There is a further need for an approach to determining a situation inwhich remote patient care is inappropriate based on a reference baselineof patient wellness. Preferably, such an approach would include a rangeof acceptance parameters as part of the reference baseline, therebyenabling those potential patients whose reference baseline falls outsidethose acceptance parameters to be identified.

SUMMARY OF THE INVENTION

The present invention provides a system and method for generatingbaseline data for automated management of cardiovascular pressure. Thepatient device information relates to individual measures recorded byand retrieved from implantable medical devices, such as IPGs andmonitors. The patient device information is received on a regular, e.g.,daily, basis as sets of collected measures, which are stored along withother patient records in a database. The information can be analyzed inan automated fashion and feedback provided to the patient at any timeand in any location.

An embodiment is a system and method for generating baseline data forautomated management of cardiovascular pressure. Collected devicemeasures are accumulated to record raw physiometry for a patient,wherein the patient is regularly monitored by an implantable medicaldevice, beginning with an initial observation period. Derived devicemeasures are generated to provide derivative physiometry determined atleast in part from the collected device measures. A patient statusindicator is determined by analyzing the collected and derived devicemeasures to diagnose a pathophysiology indicative of an absence, onset,progression, regression, and status quo in cardiovascular pressure,wherein the collected and derived device measures and the patient statusindicator originating from the initial observation period includebaseline data.

The present invention provides a meaningful, quantitative measure ofpatient wellness for use as a reference baseline in an automated systemand method for continuous, remote patient care. The reference baselineincreases the accuracy of remote patient care, particularly during thefirst few weeks of care, by providing a grounded starting assessment ofthe patient's health and well-being.

A collateral benefit of the reference baseline is the removal ofphysician “bias” which can occur when the apparent normal outwardappearance of a patient belies an underlying condition that potentiallyrequires medical attention. The reference baseline serves to objectify apatient's self-assessment of wellness.

The present invention also provides an objective approach to humanizingthe raw measures recorded by medical devices, including implantablemedical devices. Using known quality of life assessment instruments, apatient can be evaluated and scored for relative quality of life at agiven point in time. The reference baseline of the present inventionprovides a means for correlating the quality of life assessment tomachine-recorded measures, thereby assisting a physician in furtheringpatient care.

Finally, the present invention improves the chronicling of legalresponsibility in patient care. A prescribed course of treatment can betraced back to a grounded point in time memorialized by the referencebaseline. Thus, a medical audit trail can be generated with a higherdegree of accuracy and certainty based on having an establishedoriginating point of reference.

Still other embodiments of the present invention will become readilyapparent to those skilled in the art from the following detaileddescription, wherein is described embodiments of the invention by way ofillustrating the best mode contemplated for carrying out the invention.As will be realized, the invention is capable of other and differentembodiments and its several details are capable of modifications invarious obvious respects, all without departing from the spirit and thescope of the present invention. Accordingly, the drawings and detaileddescription are to be regarded as illustrative in nature and not asrestrictive.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A and 1B are block diagrams showing a system for determining areference baseline of individual patient status for use in an automatedcollection and analysis patient care system in accordance with thepresent invention;

FIG. 2 is a block diagram showing the hardware components of the serversystem of the system of FIG. 1A;

FIG. 3 is a block diagram showing the software modules of the serversystem of the system of FIG. 1A;

FIG. 4 is a block diagram showing the processing module of the serversystem of FIG. 1A;

FIG. 5 is a database schema showing, by way of example, the organizationof a reference baseline record for cardiac patient care stored as partof a patient care record in the database of the system of FIG. 1A;

FIG. 6 is a database schema showing, by way of example, the organizationof a reference baseline quality of life record for cardiac patient carestored as part of a patient care record in the database of the system ofFIG. 1A;

FIG. 7 is a database schema showing, by way of example, the organizationof a monitoring record for cardiac patient care stored as part of apatient care record in the database of the system of FIG. 1A;

FIGS. 8A-8C are flow diagrams showing a method for determining areference baseline for use in monitoring a patient status in anautomated collection and analysis patient care system in accordance withthe present invention; and

FIG. 9 is a flow diagram showing the routine for processing a referencebaseline for use in the method of FIGS. 8A-8C;

FIG. 10 is a flow diagram showing the routine for processing quality oflife measures for use in the method of FIGS. 8A-8C; and

FIG. 11 is a flow diagram showing the routine for reassessing a newreference baseline for use in the method of FIGS. 8A-8C.

DETAILED DESCRIPTION

FIG. 1A is a block diagram showing a system 10 for determining areference baseline 5 of patient status for an individual patient 11 foruse in an automated collection and analysis patient care system inaccordance with the present invention. An automated collection andanalysis patient care system suitable for use with the present inventionis disclosed in the related, commonly-owned U.S. Pat. No. 6,312,378,issued Nov. 6, 2001, the disclosure of which is incorporated herein byreference. A patient 11 is a recipient of an implantable medical device12, such as, by way of example, an IPG or a heart failure or eventmonitor, with a set of leads extending into his or her heart.Alternatively, subcutaneous monitors or devices inserted into otherorgans (not shown) without leads could also be used. The implantablemedical device 12 includes circuitry for recording into a short-term,volatile memory telemetered signals, which are stored as a set ofcollected measures for later retrieval.

For an exemplary cardiac implantable medical device, the telemeteredsignals non-exclusively present patient information recorded on a perheartbeat, binned average or derived basis and relating to: atrialelectrical activity, ventricular electrical activity, minuteventilation, patient activity score, cardiac output score, mixed venousoxygenation score, cardiovascular pressure measures, time of day, thenumber and types of interventions made, and the relative success of anyinterventions, plus the status of the batteries and programmed settings.Examples of pacemakers suitable for use in the present invention includethe Discovery line of pacemakers, manufactured by Guidant Corporation,Indianapolis, Ind. Examples of ICDs suitable for use in the presentinvention include the Gem line of ICDs, manufactured by MedtronicCorporation, Minneapolis, Minn.

In the described embodiment, the patient 11 has a cardiac implantablemedical device. However, a wide range of related implantable medicaldevices are used in other areas of medicine and a growing number ofthese devices are also capable of measuring and recording patientinformation for later retrieval. These implantable medical devicesinclude monitoring and therapeutic devices for use in metabolism,endocrinology, hematology, neurology, muscular disorders,gastroenterology, urology, ophthalmology, otolaryngology, orthopedics,and similar medical subspecialties. One skilled in the art would readilyrecognize the applicability of the present invention to these relatedimplantable medical devices.

The telemetered signals stored in the implantable medical device 12 areretrieved upon completion of an initial observation period andsubsequently retrieved on a continuous, periodic basis. By way ofexample, a programmer 14 can be used to retrieve the telemeteredsignals. However, any form of programmer, interrogator, recorder,monitor, or telemetered signals transceiver suitable for communicatingwith an implantable medical device 12 could be used, as is known in theart. In addition, a personal computer or digital data processor could beinterfaced to the implantable medical device 12, either directly or viaa telemetered signals transceiver configured to communicate with theimplantable medical device 12.

Using the programmer 14, a magnetized reed switch (not shown) within theimplantable medical device 12 closes in response to the placement of awand 14 over the location of the implantable medical device 12. Theprogrammer 14 communicates with the implantable medical device 12 via RFsignals exchanged through the wand 14. Programming or interrogatinginstructions are sent to the implantable medical device 12 and thestored telemetered signals are downloaded into the programmer 14. Oncedownloaded, the telemetered signals are sent via an internetwork 15,such as the Internet, to a server system 16 which periodically receivesand stores the telemetered signals in a database 17, as furtherdescribed below with reference to FIG. 2.

An example of a programmer 14 suitable for use in the present inventionis the Model 2901 Programmer Recorder Monitor, manufactured by GuidantCorporation, Indianapolis, Ind., which includes the capability to storeretrieved telemetered signals on a proprietary removable floppydiskette. The telemetered signals could later be electronicallytransferred using a personal computer or similar processing device tothe internetwork 15, as is known in the art.

Other alternate telemetered signals transfer means could also beemployed. For instance, the stored telemetered signals could beretrieved from the implantable medical device 12 and electronicallytransferred to the internetwork 15 using the combination of a remoteexternal programmer and analyzer and a remote telephonic communicator,such as described in U.S. Pat. No. 5,113,869, the disclosure of which isincorporated herein by reference. Similarly, the stored telemeteredsignals could be retrieved and remotely downloaded to the server system16 using a world-wide patient location and data telemetry system, suchas described in U.S. Pat. No. 5,752,976, the disclosure of which isincorporated herein by reference.

The initial set of telemetered signals recorded during the initialobservation period is processed by the server system 16 into a set ofreference measures and stored as a reference baseline 5 in the database17, as further described below with reference to FIG. 3. The purpose ofthe observation period is to establish a reference baseline 5 containinga set of reference measures that can include both measured and derivedpatient information. The reference baseline 5 can link “hard”machine-recorded data with “soft” patient-provided self-assessment datafrom which can be generated a wellness status indicator. In addition,the reference baseline 5 can be used to identify patients for whomremote patient care may be inappropriate and for patient wellnesscomparison and analysis during subsequent, on-going remote patient care.The reference baseline 5 is maintained in the database 17 and can bereassessed as needed or on a periodic basis.

Subsequent to the initial observation period, the patient is remotelymonitored by the server system 16 through the periodic receipt oftelemetered signals from the implantable medical device 12 via theinternetwork 15. Feedback is then provided back to the patient 11through a variety of means. By way of example, the feedback can be sentas an electronic mail message generated automatically by the serversystem 16 for transmission over the internetwork 15. The electronic mailmessage is received by personal computer 18 (PC) situated for localaccess by the patient 11. Alternatively, the feedback can be sentthrough a telephone interface device 19 as an automated voice mailmessage to a telephone 21 or as an automated facsimile message to afacsimile machine 22, both also situated for local access by the patient11. In addition to a personal computer 18, telephone 21, and facsimilemachine 22, feedback could be sent to other related devices, including anetwork computer, wireless computer, personal data assistant,television, or digital data processor.

FIG. 1B is a block diagram showing a further embodiment of the presentinvention in which the patient 11 is monitored by the implantablemedical device 12 while engaged in performing a prescribed set of timedphysical stressors during an initial observation period or during asubsequent observation period if the patient 11 is being reassessed. Thestressors are a set of normal, patient activities and cardiovascular andrespiratory maneuvers that allow consistent, reproducible physiologicalfunctions to be measured by the implantable medical device 12. Thesemaneuvers include activities such as a change in posture, simplephysical exercises, breathing state, including holding breath andhyperventilating, and oxygen challenges. By way of example, thestressors include timed physical activities such as running in place 6,recumbency 7, standing 8, sitting motionless 9, and reprogramming atleast one of pacing interventions and pacing modes of the implantablemedical device 12, as further described below with reference to FIG. 5.

In a still further embodiment of the present invention, at least one ofpacing interventions and pacing modes of the implantable medical device12 is reprogrammed by the programmer 14 during the initial observationperiod or during a subsequent observation period if the patient 11 isbeing reassessed. The patient 11 is then monitored by the reprogrammedimplantable medical device 12.

FIG. 2 is a block diagram showing the hardware components of the serversystem 16 of the system 10 of FIG. 1A. The server system 16 consists ofthree individual servers: network server 31, database server 34, andapplication server 35. These servers are interconnected via anintranetwork 33. In the described embodiment, the functionality of theserver system 16 is distributed among these three servers for efficiencyand processing speed, although the functionality could also be performedby a single server or cluster of servers. The network server 31 is theprimary interface of the server system 16 onto the internetwork 15. Thenetwork server 31 periodically receives the collected telemeteredsignals sent by remote implantable medical devices over the internetwork15. The network server 31 is interfaced to the internetwork 15 through arouter 32. To ensure reliable data exchange, the network server 31implements a TCP/IP protocol stack, although other forms of networkprotocol stacks are suitable.

The database server 34 organizes the patient care records in thedatabase 17 and provides storage of and access to information held inthose records. A high volume of data in the form of collected devicemeasures sets from individual patients is received. The database server34 frees the network server 31 from having to categorize and store theindividual collected device measures sets in the appropriate patientcare record.

The application server 35 operates management applications, assimilatesthe reference measures into the reference baseline 5 (shown in FIG. 1A),and performs data analysis of the patient care records, as furtherdescribed below with reference to FIG. 3. The application server 35communicates feedback to the individual patients either throughelectronic mail sent back over the internetwork 15 via the networkserver 31 or as automated voice mail or facsimile messages through thetelephone interface device 19.

The server system 16 also includes a plurality of individualworkstations 36 (WS) interconnected to the intranetwork 33, some ofwhich can include peripheral devices, such as a printer 37. Theworkstations 36 are for use by the data management and programmingstaff, nursing staff, office staff, and other consultants and authorizedpersonnel.

The database 17 consists of a high-capacity storage medium configured tostore individual patient care records and related health careinformation. Preferably, the database 17 is configured as a set ofhigh-speed, high capacity hard drives, such as organized into aRedundant Array of Inexpensive Disks (RAID) volume. However, any form ofvolatile storage, non-volatile storage, removable storage, fixedstorage, random access storage, sequential access storage, permanentstorage, erasable storage, and the like would be equally suitable. Theorganization of the database 17 is further described below withreference to FIGS. 5-7.

The individual servers and workstations are general purpose, programmeddigital computing devices consisting of a central processing unit (CPU),random access memory (RAM), non-volatile secondary storage, such as ahard drive or CD ROM drive, network interfaces, and peripheral devices,including user interfacing means, such as a keyboard and display.Program code, including software programs, and data are loaded into theRAM for execution and processing by the CPU and results are generatedfor display, output, transmittal, or storage. In the describedembodiment, the individual servers are Intel Pentium-based serversystems, such as available from Dell Computers, Austin, Tex., or CompaqComputers, Houston, Tex. Each system is preferably equipped with 128 MBRAM, 100 GB hard drive capacity, data backup facilities, and relatedhardware for interconnection to the intranetwork 33 and internetwork 15.In addition, the workstations 36 are also Intel Pentium-based personalcomputer or workstation systems, also available from Dell Computers,Austin, Tex., or Compaq Computers, Houston, Tex. Each workstation ispreferably equipped with 64 MB RAM, 10 GB hard drive capacity, andrelated hardware for interconnection to the intranetwork 33. Other typesof server and workstation systems, including personal computers,minicomputers, mainframe computers, supercomputers, parallel computers,workstations, digital data processors and the like would be equallysuitable, as is known in the art.

The telemetered signals are communicated over an internetwork 15, suchas the Internet. However, any type of electronic communications linkcould be used, including an intranet work link, serial link, datatelephone link, satellite link, radio-frequency link, infrared link,fiber optic link, coaxial cable link, television link, and the like, asis known in the art. Also, the network server 31 is interfaced to theinternetwork 15 using a T-1 network router 32, such as manufactured byCisco Systems, Inc., San Jose, Calif. However, any type of interfacingdevice suitable for interconnecting a server to a network could be used,including a data modem, cable modem, network interface, serialconnection, data port, hub, frame relay, digital PBX, and the like, asis known in the art.

FIG. 3 is a block diagram showing the software modules of the serversystem 16 of the system 10 of FIG. 1A. Each module is a computer programwritten as source code in a conventional programming language, such asthe C or Java programming languages, and is presented for execution bythe CPU as object or byte code, as is known in the art. The variousimplementations of the source code and object and byte codes can be heldon a computer-readable storage medium or embodied on a transmissionmedium in a carrier wave.

There are three basic software modules, which functionally define theprimary operations performed by the server system 16: database module51, analysis module 53, and processing module 56. In the describedembodiment, these modules are executed in a distributed computingenvironment, although a single server or a cluster of servers could alsoperform the functionality of these modules. The module functions arefurther described below beginning with reference to FIGS. 8A-8C.

A reference baseline 5 is established at the outset of providing apatient with remote patient care. The server system 16 periodicallyreceives an initially collected device measures set 57. This setrepresents patient information, which was collected from the implantablemedical device 12 (shown in FIG. 1A) during the initial observationperiod, as further discussed below with reference to FIG. 5. Inaddition, the server system 16 can also periodically receive quality oflife measures sets 60 recorded by the patient 11, as further describedbelow with reference to FIG. 6. Both the initially collected devicemeasures set 57 and quality of life measures set 60 are forwarded to thedatabase module 51 for storage in the patient's patient care record inthe database 52. During subsequent, on-going monitoring for remotepatient care, the server system 16 periodically receives subsequentlycollected device measures sets 58, which are also forwarded to thedatabase module 51 for storage.

The database module 51 organizes the individual patent care recordsstored in the database 52 and provides the facilities for efficientlystoring and accessing the collected device measures sets 57, 58 andpatient data maintained in those records. Exemplary database schemes foruse in storing the initially collected device measures set 57, qualityof life measures set 60, and subsequently collected device measures sets58 in a patient care record are described below, by way of example, withreference to FIGS. 5-7. The database server 34 (shown in FIG. 2)performs the functionality of the database module 51. Any type ofdatabase organization could be utilized, including a flat file system,hierarchical database, relational database, or distributed database,such as provided by database vendors, such as Oracle Corporation,Redwood Shores, Calif.

The processing module 56 processes the initially collected devicemeasures set 57 and, if available, the quality of life measures set 60,stored in the patient care records in the database 52 into the referencebaseline 5. The reference baseline 5 includes a set of referencemeasures 59 which can be either directly measured or indirectly derivedpatient information. The reference baseline 5 can be used to identifypatients for whom remote patient care might be inappropriate and tomonitor patient wellness in a continuous, on-going basis.

On a periodic basis or as needed, the processing module 56 reassessesthe reference baseline 5. Subsequently collected device measures sets 58are received from the implantable medical device 12 (shown in FIG. 1A)subsequent to the initial observation period. The processing module 56reassimilates these additional collected device measures sets into a newreference baseline. The operations performed by the processing module 56are further described below with reference to FIG. 4. The applicationserver 35 (shown in FIG. 2) performs the functionality of the processingmodule 56.

The analysis module 53 analyzes the subsequently collected devicemeasures sets 58 stored in the patient care records in the database 52.The analysis module 53 monitors patient wellness and makes an automateddetermination in the form of a patient status indicator 54. Subsequentlycollected device measures sets 58 are periodically received fromimplantable medical devices and maintained by the database module 51 inthe database 52. Through the use of this collected information, theanalysis module 53 can continuously follow the medical well being of apatient and can recognize any trends in the collected information thatmight warrant medical intervention. The analysis module 53 comparesindividual measures and derived measures obtained from both the carerecords for the individual patient and the care records for a diseasespecific group of patients or the patient population in general. Theanalytic operations performed by the analysis module 53 are furtherdescribed below with reference to FIG. 4. The application server 35(shown in FIG. 2) performs the functionality of the analysis module 53.

The feedback module 55 provides automated feedback to the individualpatient based, in part, on the patient status indicator 54. As describedabove, the feedback could be by electronic mail or by automated voicemail or facsimile. Preferably, the feedback is provided in a tieredmanner. In the described embodiment, four levels of automated feedbackare provided. At a first level, an interpretation of the patient statusindicator 54 is provided. At a second level, a notification of potentialmedical concern based on the patient status indicator 54 is provided.This feedback level could also be coupled with human contact byspecially trained technicians or medical personnel. At a third level,the notification of potential medical concern is forwarded to medicalpractitioners located in the patient's geographic area. Finally, at afourth level, a set of reprogramming instructions based on the patientstatus indicator 54 could be transmitted directly to the implantablemedical device to modify the programming instructions contained therein.As is customary in the medical arts, the basic tiered feedback schemewould be modified in the event of bona fide medical emergency. Theapplication server 35 (shown in FIG. 2) performs the functionality ofthe feedback module 55.

FIG. 4 is a block diagram showing the processing module 56 of the serversystem 16 of FIG. 1A. The processing module 53 contains two functionalsubmodules: evaluation module 70 and acceptance module 71. The purposeof the evaluation module 70 is to process the initially collected devicemeasures set 57 by determining any derived measures and calculatingappropriate statistical values, including means and standard deviations,for the reference measures set 59 in the reference baseline 5. Thepurpose of the acceptance module 71 is to analyze the reference measuresset 59 against the acceptance parameters set 72. A patient care recordstoring a reference measures set 59 substantially out of conformity withthe acceptance parameters set 72 could be indicative of a patient forwhom remote patient care is inappropriate. Consequently, the acceptancemodule 71 identifies each patient care record storing at least onereference measure which is substantially non-conforming to acorresponding parameter in the acceptance parameters set 72.

For instance, an acceptance parameter for heart rate might be specifiedas a mean heart rate within a range of 40-90 beats per minute (bpm) overa 24-hour period. However, a patient care record storing a referencemeasure falling either substantially above or below this acceptanceparameter, for example, in excess of 90 bpm, would be consideredsubstantially non-conforming. The acceptance parameters set 72 arefurther described below with reference to FIG. 5.

The evaluation module 70 also determines new reference baselines 73 whennecessary. For instance, the new reference baseline 73 might bereassessed on an annual or quarterly basis, as the needs of the patient11 dictate. Similarly, the new reference baseline 73 might be reassessedfor a patient whose patient care record stores a subsequently collecteddevice measures set 58 substantially out of conformity with thereference measures set 59 in the original reference baseline 5. The newreference baseline 73 would be assessed by the processing module 56using subsequently collected device measures sets 58 during a subsequentobservation period.

FIG. 5 is a database schema showing, by way of example, the organizationof a reference baseline record 75 for cardiac patient care stored aspart of a patient care record in the database 17 of the system 10 ofFIG. 1A. The reference baseline record 75 corresponds to the referencebaseline 5, although only the information pertaining to the set ofreference measures in the reference baseline 5 are shown. Each patientcare record would also contain normal identifying and treatment profileinformation, as well as medical history and other pertinent data (notshown). For instance, during the initial observation period, the patient11 maintains a diary of activities, including the onset of bedtime andwaking time, plus the time and dosing of any medications, includingnon-prescription drugs. The observation period can be expanded toinclude additional information about the normal range of patientactivities as necessary, including a range of potential anticipatedactivities as well as expected travel times and periods away from home.In addition, information from any set of medical records could beincluded in the patient care record. The diary, medication, activity,and medical record information and medical test information (e.g.,electrocardiogram, echocardiogram, and/or coronary angiogram) isincorporated into the patient care record and is updated with continuingpatient information, such as changes in medication, as is customary inthe art.

The reference measures set 59 stored in the reference baseline record 75are processed from the initial collected device measures set 57 (shownin FIG. 3), as further described below with reference to FIG. 9. Theimplantable medical device 12 (shown in FIG. 1A) records the initialcollected device measures set 57 during the initial observation period.For example, for a cardiac patient, the reference baseline record 75stores the following information as part of the reference measures set59: patient activity score 76, posture 77 (e.g., from barometricpressure), atrial electrical activity 78 (e.g., atrial rate),ventricular electrical activity 79 (e.g., ventricular rate),cardiovascular pressures 80, cardiac output 81, oxygenation score 82(e.g., mixed venous oxygenation), pulmonary measures 83 (e.g.,transthoracic impedance, measures of lung wetness, and/or minuteventilation), body temperature 84, PR interval 85 (or AV interval), QRSmeasures 86 (e.g., width, amplitude, frequency content, and/ormorphology), QT interval 87, ST-T wave measures 88 (e.g., T wavealternans or ST segment depression or elevation), potassium [K+] level89, sodium [Na+] level 90, glucose level 91, blood urea nitrogen andcreatinine 92, acidity (pH) level 93, hematocrit 94, hormonal levels 95(e.g., insulin, epinephrine), cardiac injury chemical tests 96 (e.g.,troponin, myocardial band creatinine kinase), myocardial blood flow 97,central nervous system injury chemical tests 98 (e.g., cerebral bandcreatinine kinase), central nervous system (CNS) blood flow 99, and timeof day 100. Other types of reference measures are possible. In addition,a well-documented set of derived measures can be determined based on thereference measures, as is known in the art.

In the described embodiment, the initial and any subsequent observationperiods last for about one 7-day period during which time the patient 11might be asked to perform, if possible, repeated physical stressorsrepresentative of both relatively normal activity and/or activitiesdesigned to test the response of the body to modest activity andphysiologic perturbations for use as the baseline “reference” measuresthat might be recorded daily for a period of one week prior toinitiating fee-for-service monitoring. Reference measures taken andderived from the observation period are recorded, processed, and storedby the system 10.

The reference measures include both measured and derived measures,including patient activity score 76, posture 77, atrial electricalactivity 78, ventricular electrical activity 79, cardiovascularpressures 80, cardiac output 81, oxygenation score 82, pulmonarymeasures 83, body temperature 84, PR interval 85 (or AV interval), QRSmeasures 86, QT interval 87, ST-T wave measures 88, potassium [K+] level89, sodium [Na+] level 90, glucose level 91, blood urea nitrogen andcreatinine 92, acidity (pH) level 93, hematocrit 94, hormonal levels 95,cardiac injury chemical tests 96, myocardial blood flow 97, centralnervous system injury chemical tests 98, central nervous system (CNS)blood flow 99, and time of day 100. Other combination and derivativemeasures can also be determined, as known in the art.

An illustrative prescribed set of timed physical stressors for anon-ambulatory patient 11 is as follows:

-   -   (1) Running in place 6: if possible, the patient 11 must run in        place for about five minutes;    -   (2) Walking (not shown): if possible, the patient 11 must walk        for about six minutes and the total distance walked is measured;    -   (3) Ascending stairs (not shown): if possible, the patient 11        must ascend two flights of stairs;    -   (4) Recumbency 7: if possible, the patient 11 must recline        following about two minutes of motionless immobile upright        posture. Upon recumbency, the patient 11 must remain as immobile        as possible for about ten minutes;    -   (5) Standing 8: if possible, the patient 11 must briskly assume        an upright standing posture after the ten-minute recumbency 7        and must remain standing without activity for about five        minutes;    -   (6) Coughing (not shown): if possible, the patient 11 must cough        forcefully about three times when in an upright position to        record the cardiovascular pressures 80;    -   (7) Hyperventilation (not shown): if possible, the patient 11        must hyperventilate over thirty seconds with full deep and rapid        breaths to record ventilatory status;    -   (8) Sitting motionless 9: when a physician is complicit, the        patient 11 must, if possible, use an approximately 2.0 liter per        minute nasal cannula while transmitting data for about twenty        minutes while sitting to evaluate cardiopulmonary response;    -   (9) Program AAI and VVI temporary pacing interventions for five        minutes, at low and high rates, if applicable (e.g., 40 bpm and        120 bpm) to evaluate cardiopulmonary response; and    -   (10) Test dual site or biventricular pacing modes, if        applicable, for approximately 20 minutes to evaluate        cardiopulmonary response.

These physical and pacing stimulus stressors must be annotated with dateand time of day 100 and correlated with symptoms and the quality of lifemeasures 110. Heart rate, temperature, and time of day are directlymeasured while the patient activity score and cardiac output score arederived. These physical stressors are merely illustrative in nature andthe set of physical and pacing stimulus stressors actually performed byany given patient would necessarily depend upon their age and physicalcondition as well as device implanted. Also, during the observationperiod, the temperature is monitored with QT interval shortening and, ifthe patient is in atrial fibrillation, the patient 11 must undergo anincremental ventricular pacing protocol to assess his or her response torate stabilization. Finally, a T-wave alternans measurement (not shown)can be integrated into the reference baseline 5 during rest and sinusrhythm activities.

In a further embodiment of the present invention, the reference measuresset 59 in the reference baseline 5 are reassessed on an annual or, ifnecessary, quarterly, basis. In addition, if the reference measures set59 was recorded during a period when the patient 11 was unstable orrecovering from a recent illness, the reference baseline 5 is reassessedwhen the patient 11 is again stable, as further described below withreference to FIG. 11.

As further described below with reference to FIG. 9, the referencemeasures are analyzed against the acceptance parameters set 72. Theacceptance parameters are those indicator values consistent with thepresence of some form of chronic yet stable disease which does notrequire immediate emergency care. In the described embodiment, theacceptance parameters set 72 for the reference measures 59 in thereference baseline record 75 are, by way of example, as follows: cardiacoutput 81 falling below 2.5 liters/minute/m²; heart rate below 40 bpm orabove 120 bpm; body temperature 84 over 101° F. and below 97° F.;patient activity 76 score of 1.0 or below; oxygenation score 82 of lessthan 60% mixed venous saturation at rest; pulmonary artery diastolicpressure greater than 20 mm Hg at rest; and minute ventilation less than10.0 liters/minute at rest.

FIG. 6 is a database schema showing, by way of example, the organizationof a reference baseline quality of life record 110 for cardiac patientcare stored as part of a patient care record in the database 17 of thesystem 10 of FIG. 1A. A quality of life score is a semi-quantitativeself-assessment of an individual patient's physical and emotional wellbeing. Non-commercial, non-proprietary standardized automated quality oflife scoring systems are readily available, such as provided by the DukeActivities Status Indicator. These scoring systems can be provided foruse by the patient 11 on the personal computer 18 (shown in FIG. 1A) andthe patient 11 can then record his or her quality of life scores forperiodic download to the server system 16.

For example, for a cardiac patient, the reference baseline quality oflife record 110 stores the following information as part of thereference measures set 59: health wellness 111, shortness of breath 112,energy level 113, exercise tolerance 114, chest discomfort 115, time ofday 116, and other quality of life measures as would be known to oneskilled in the art. Using the quality of life scores 111-116 in thereference baseline quality of life record 110, the patient 11 can benotified automatically when variable physiological changes matches hisor her symptomatology.

A quality of life indicator is a vehicle through which a patient canremotely communicate to the patient care system how he or she issubjectively feeling. When tied to machine-recorded physiologicalmeasures, a quality of life indicator can provide valuable additionalinformation to medical practitioners and the automated collection andanalysis patient care system 10 not otherwise discernible without havingthe patient physically present. For instance, a scoring system using ascale of 1.0 to 10.0 could be used with 10.0 indicating normal wellnessand 1.0 indicating severe health problems. Upon the completion of theinitial observation period, a patient might indicate a health wellnessscore 111 of 5.0 and a cardiac output score of 5.0. After one month ofremote patient care, the patient might then indicate a health wellnessscore 111 of 4.0 and a cardiac output score of 4.0 and a week laterindicate a health wellness score 111 of 3.5 and a cardiac output scoreof 3.5. Based on a comparison of the health wellness scores 111 and thecardiac output scores, the system 10 would identify a trend indicatingthe necessity of potential medical intervention while a comparison ofthe cardiac output scores alone might not lead to the same prognosis.

FIG. 7 is a database schema showing, by way of example, the organizationof a monitoring record 120 for cardiac patient care stored as part of apatient care record in the database 17 of the system 10 of FIG. 1A. Eachpatient care record stores a multitude of subsequently collected devicemeasures sets 58 (shown in FIG. 3) for each individual patient 11. Eachset represents a recorded snapshot of telemetered signals data whichwere recorded, for instance, on a per heartbeat or binned average basisby the implantable medical device 12. For example, for a cardiacpatient, the following information would be recorded as a subsequentlycollected device measures set 58: atrial electrical activity 121,ventricular electrical activity 122, minute ventilation 123, patientactivity score 124, cardiac output score 125, mixed venous oxygen score126, pulmonary artery diastolic pressure measure 127, time of day 128,interventions made by the implantable medical device 129, and therelative success of any interventions made 130. In addition, theimplantable medical device 12 would also communicate device specificinformation, including battery status and program settings 131. Othertypes of collected or combined measures are possible as previouslydescribed. In addition, a well-documented set of derived measures can bedetermined based on the collected measures, as is known in the art.

FIGS. 8A-8C are flow diagrams showing a method 140 for determining areference baseline 5 for use in monitoring a patient status in anautomated collection and analysis patient care system 10 in accordancewith the present invention. The method 140 operates in two phases:collection and processing of an initial reference baseline 5 (blocks141-149) and monitoring using the reference baseline 5 (blocks 150-158).The method 140 is implemented as a conventional computer program forexecution by the server system 16 (shown in FIG. 1A). As a preparatorystep, the patient care records are organized in the database 17 with aunique patient care record assigned to each individual patient (block141).

The collection and processing of the initial reference baseline 5 beginswith the patient 11 being monitored by the implantable medical device 12(shown in FIG. 1A). The implantable medical device 12 records theinitially collected device measures set 57 during the initialobservation period (block 142), as described above with reference toFIG. 5. Alternatively, the patient 11 could be engaged in performing theprescribed set of timed physical stressors during the initialobservation period, as described above with reference to FIG. 1B. Aswell, the implantable medical device 12 could be reprogrammed by theprogrammer 14 during the initial observation period, also as describedabove with reference to FIG. 1B. The initially collected device measuresset 57 is retrieved from the implantable medical device 12 (block 143)using a programmer, interrogator, telemetered signals transceiver, andthe like. The retrieved initially collected device measures sets aresent over the internetwork 15 or similar communications link (block 144)and periodically received by the server system 16 (block 145). Theinitially collected device measures set 57 is stored into a patient carerecord in the database 17 for the individual patient 11 (block 146). Theinitially collected device measures set 57 is processed into thereference baseline 5 (block 147) which stores a reference measures set59, as further described below with reference to FIG. 9.

If quality of life measures are included as part of the referencebaseline 5 (block 148), the set of quality of life measures areprocessed (block 149), as further described below with reference to FIG.10. Otherwise, the processing of quality of life measures is skipped(block 148).

Monitoring using the reference baseline 5 begins with the retrieval ofthe subsequently collected device measures sets 58 from the implantablemedical device 12 (block 150) using a programmer, interrogator,telemetered signals transceiver, and the like. The subsequentlycollected device measures sets 58 are sent, on a substantially regularbasis, over the internetwork 15 or similar communications link (block151) and periodically received by the server system 16 (block 152). Thesubsequently collected device measures sets 58 are stored into thepatient care record in the database 17 for that individual patient(block 153).

The subsequently collected device measures sets 58 are compared to thereference measures in the reference baseline 5 (block 154). If thesubsequently collected device measures sets 58 are substantiallynon-conforming (block 155), the patient care record is identified (block156). Otherwise, monitoring continues as before.

In the described embodiment, substantial non-conformity refers to asignificant departure from a set of parameters defining ranges ofrelative normal activity and normal exercise responses for that patient.Relative normal activity is defined as follows. Note the “test exerciseperiod” refers to running in place, walking, and ascending stairsphysical stressors described above:

-   -   (1) Heart rate stays within a range of 40-90 bpm without upward        or downward change in mean heart rate ±1.0 standard deviation        (SD) over a 24 hour period;    -   (2) Wake patient activity score during awake hours stays within        a range of ±1.0 SD without change in the mean activity score        over a 24 hour period with no score equal to the minimum        activity score noted during sleep;    -   (3) Sleep period activity score stays within a range of ±1.0 SD        of typical sleep scores for that patient for the six to ten hour        period of sleep with no score less than the minimum score        observed during normal awake behavior during the initial        observation period or during normal sleep;    -   (4) Minute ventilation 123 during normal awake hours stays        within a range of ±1.0 SD without change in the mean score over        a 24 hour period with no score equal to the minimum or maximum        minute ventilation 123 noted during the test exercise period or        the minimum or maximum minute ventilation 123 noted during the        initial observation period;    -   (5) Cardiac output score 125 during normal awake hours stays        within a range of ±1.0 SD without change in the mean cardiac        output score over a 24 hour period with no score equal to the        minimum cardiac output score noted during the test exercise        period or the minimum cardiac output score noted during the        initial observation period;    -   (6) Mixed venous oxygenation score 126 during normal awake hours        stays within a range of ±1.0 SD without change in the mean mixed        venous oxygenation score over a 24 hour period with no score        equal to the minimum mixed venous oxygenation score noted during        the test exercise period or the minimum mixed venous oxygenation        score noted during the initial observation period;    -   (7) Pulmonary artery diastolic pressure measure 127 during        normal awake hours stays within a range of ±1.0 SD without        change in the mean pulmonary artery diastolic pressure measure        127 over a 24 hour period with no score equal to the minimum or        maximum pulmonary artery diastolic pressure measure 127 noted        during the test exercise period or during the initial        observation period;    -   (8) Potassium levels [K+] score during normal awake hours stays        within a range of ±1.0 SD without change in the mean K+ levels        over a 24 hour period with no score less than 3.5 meq/liter or        greater than 5.0 meq/liter noted during the test exercise period        or during the initial observation period;    -   (9) Sodium levels [Na+] score during normal awake hours stays        within a range of ±1.0 SD without change in the mean Na+ levels        over a 24 hour period with no score less than 135 meq/liter or        greater than 145 meq/liter during the test exercise period or        during the initial observation period;    -   (10) Acidity (pH) score during normal awake hours stays within a        range of ±1.0 SD without change in the mean pH score over a 24        hour period with no score equal to the minimum or maximum pH        score noted during the test exercise period or the minimum or        maximum pH scores noted during the initial observation period;    -   (11) Glucose levels during normal awake hours stays within a        range of ±1.0 SD without change in the mean glucose levels over        a 24 hour period with no score less than 60 mg/dl or greater        than 200 mg/dl during the test exercise period or during the        initial observation period;    -   (12) Blood urea nitrogen (BUN) or creatinine (Cr) levels during        normal awake hours stays within a range of ±1.0 SD without        change in the mean BUN or Cr levels score over a 24 hour period        with no score equal to the maximum BUN or creatinine levels        noted during the test exercise period or the maximum BUN or Cr        levels noted during the initial observation period;    -   (13) Hematocrit levels during normal awake hours stays within a        range of ±1.0 SD without change in the mean hematocrit levels        score over a 24 hour period with no score less than a hematocrit        of 30 during the test exercise period or during the initial        observation period;    -   (14) Troponin, creatinine kinase myocardial band, or other        cardiac marker of myocardial infarction or ischemia, level        during normal awake hours stays within a range of ±1.0 SD        without change in the mean troponin level score over a 24 hour        period with no score equal to the maximum troponin level score        noted during the test exercise period or the maximum troponin        level scores noted during the initial observation period;    -   (15) Central nervous system (CNS) creatinine kinase (CK) or        equivalent markers of CNS ischemia or infarction levels during        normal awake hours stays within a range of ±1.0 SD without        change in the mean CNS CK levels over a 24 hour period with no        score equal to the maximum CNS CK levels score noted during the        test exercise period or the maximum CNS CK levels scores noted        during the initial observation period;    -   (16) Barometric pressure during normal awake hours stays within        a range of ±1.0 SD without change in the mean barometric        pressure score over a 24 hour period with no score equal to the        minimum or maximum barometric pressure noted during the test        exercise period or the minimum or maximum barometric pressure        noted during the initial observation period;    -   (17) PR interval (or intrinsic AV interval) of sinus rhythm        during normal awake hours stays within a range of ±1.0 SD        without change in the mean PR interval over a 24 hour period        with no score equal to the minimum or maximum PR interval noted        during the test exercise period or the minimum or maximum PR        interval noted during the initial observation period;    -   (18) QT interval during normal awake hours stays within a range        of ±1.0 SD without change in the mean QT interval over a 24 hour        period with no score equal to the minimum or maximum QT interval        noted during the test exercise period or the minimum or maximum        QT interval noted during the initial observation period;    -   (19) QRS duration during normal awake hours stays within a range        of ±1.0 SD without change in the mean QRS duration over a 24        hour period with no score equal to the maximum QRS duration        noted during the test exercise period or the maximum QRS        duration noted during the initial observation period;    -   (20) ST segment depression or elevation during normal awake        hours stays within a range of ±1.0 SD without change in the mean        ST segment depression or elevation over a 24 hour period with no        score equal to the maximum ST segment depression or elevation        noted during the test exercise period or the maximum ST segment        depression or elevation noted during the initial observation        period; and    -   (21) Temperature during normal awake hours stays within a range        of ±1.0 SD without change in the mean temperature over a 24 hour        period with no score equal to the minimum or maximum temperature        score noted during the test exercise period or the minimum or        maximum temperature noted during the initial observation period.

For an exemplary, non-ambulatory patient with no major impairments ofthe major limbs, reference exercise can be defined as follows:

-   -   (1) Heart rate increases by 10 bpm for each one point increase        in activity score. Note that to be considered “normal exercise,”        heart rate generally should not increase when the activity score        does not increase at least 1.0 SD above that noted during the        twenty-four hour reference period or greater than that observed        during any reference exercise periods. Heart rate should        decrease to the baseline value over fifteen minutes once        activity stops or returns to the baseline activity level;    -   (2) Patient activity score 124 rises at least 1.0 SD over that        observed in the mean activity score over a 24 hour period or        greater than that observed during any reference exercise        periods;    -   (3) Cardiac output score 125 rises at least 1.0 SD over that        observed in the mean cardiac output score over a 24 hour period        or within 0.5 SD of the two minute test exercise period. Cardiac        output score should increase 0.5 liters per minute with each 10        bpm increase in heart rate period or greater than that observed        during any reference exercise periods;    -   (4) In conjunction with an increase in activity score and heart        rate, mixed venous oxygenation score 126 falls at least 1.0 SD        below observed in the mean oxygenation score over a 24 hour        period or be less than any oxygenation score observed during the        reference exercise periods. Oxygenation score should decrease        5.0 mm Hg with each 10 bpm increase in heart rate or 1.0 SD        increase in cardiac output score during exercise;    -   (5) In conjunction with an increase in activity score and heart        rate, pulmonary artery diastolic pressure measure 127 rises at        least 1.0 SD over that observed in the mean cardiovascular        pressure score over a 24 hour period or is greater than that        observed during the reference exercise periods;    -   (6) In conjunction with an increase in activity score and heart        rate, minute ventilation 123 rises at least 1.0 SD over that        observed over a 24 hour reference period or greater than that        observed during any reference exercise period. Minute        ventilation should rise 1.0 liter per minute with each 10 bpm        increase in heart rate; and    -   (7) In conjunction with an increase in activity score and heart        rate, temperature should rise at least 1.0 SD over that observed        in the mean temperature over a 24 hour period or greater than        that observed during the reference exercise periods. Temperature        should rise 0.1° F. with each 10 bpm increase in heart rate.

Finally, if the time for a periodic reassessment has arrived or thesubsequently collected device measures sets 58 are substantiallynon-conforming (block 157), the reference baseline 5 is reassessed(block 158) and a new reference baseline 73 determined, as furtherdescribed below with reference to FIG. 11. Otherwise, the routinereturns.

In the described embodiment, the reference baseline 5 is preferablyreassessed on an annual or, if necessary, quarterly basis. In addition,the reference baseline 5 might be reassessed if physiological findingsdictate that new interventions might be indicated or if the patient 11indicates a change in medications and general health status. Other basesfor reassessing the reference baseline 5 are feasible.

FIG. 9 is a flow diagram showing the routine 147 for processing areference baseline 5 for use in the method 140 of FIGS. 8A-8C. Thepurpose of this routine is to analyze the initially collected devicemeasures set 57 and create a reference baseline 5, if possible. First,the acceptance parameters set 72 (shown in FIG. 3) is defined (block160) and the reference measures set 59 in the reference baseline 5,including any quality of life measures, are analyzed against theacceptance parameters set (block 161), as described above with referenceto FIG. 5. If the reference measures in the reference baseline 5 aresubstantially non-conforming to the acceptance parameters set (block162), the patient care record is identified (block 164). Otherwise, ifconforming (block 162), the baseline reference 72 is stored into thepatient care record in the database 17 (block 163). The routine thenreturns.

FIG. 10 is a flow diagram showing the routine 149 for processing qualityof life measures for use in the method 140 of FIGS. 8A-8C. The purposeof this routine is to process and store a collected quality of lifemeasures set 60 into the reference baseline 5. Collected quality of lifemeasures sets 60 are periodically received by the server system 16 overthe internetwork 15 or similar communications link (block 170). Thequality of life measures were previously recorded by the patient 11using, for example, the personal computer 18 (shown in FIG. 1A) anddownloaded onto the internetwork 15 or similar communications link. Thecollected quality of life measures set 60 is stored into a patient carerecord in the database 17 for the individual patient 11 (block 171). Thecollected quality of life measures set 60 is then assimilated into thereference baseline 5 (block 172), as further described above withreference to FIG. 9. The routine then returns.

FIG. 11 is a flow diagram showing the routine 158 for reassessing a newreference baseline 73 for use in the method 140 of FIGS. 8A-8C. Thepurpose of this routine is to reassess a new reference baseline 5periodically or when necessary. Similar to the collection andassimilation of the initial reference baseline 5, the routine beginswith the patient 11 being monitored by the implantable medical device 12(shown in FIG. 1A). The implantable medical device 12 recordssubsequently collected device measures sets 58 throughout a subsequentobservation period (block 180), as described above with reference toFIG. 5. Alternatively, the patient 11 could be engaged in performing theprescribed set of timed physical stressors, as described above withreference to FIG. 1B. As well, the implantable medical device 12 couldbe reprogrammed by the programmer 14 during the subsequent observationperiod, also as described above with reference to FIG. 1B. Thesubsequently collected device measures sets 58 are retrieved from theimplantable medical device 12 (block 181) using a programmer,interrogator, telemetered signals transceiver, and the like. Theretrieved subsequently collected device measures sets are sent over theinternetwork 15 or similar communications link (block 182) andperiodically received by the server system 16 (block 183). Thesubsequently collected device measures sets 58 are stored into thepatient care record in the database 17 for the individual patient 11(block 184). Finally, the subsequently collected device measures sets 58are assimilated into the new reference baseline 73 (block 185), asfurther described above with reference to FIG. 9. The routine thenreturns.

The determination of a reference baseline consisting of referencemeasures makes possible improved and more accurate treatmentmethodologies based on an algorithmic analysis of the subsequentlycollected data sets. Each successive introduction of a new collecteddevice measures set into the database server would help to continuallyimprove the accuracy and effectiveness of the algorithms used.

While the invention has been particularly shown and described asreferenced to the embodiments thereof, those skilled in the art willunderstand that the foregoing and other changes in form and detail maybe made therein without departing from the spirit and scope of theinvention.

1. A programmer for generating baseline data for automated management ofcardiovascular pressure, comprising: a memory to store device measuresreceived from an implantable medical device, comprising: collecteddevice measures to record raw physiometry for a patient regularlymonitored by the implantable medical device, beginning with an initialobservation period; and derived device measures to provide derivativephysiometry determined at least in part from the collected devicemeasures; and a processor to determine a wellness indicator throughanalysis of the collected and derived device measures to diagnose apatient status indicative of at least one of a change and a status quoin cardiovascular pressure, wherein the collected and derived devicemeasures and the wellness indicator originating from the initialobservation period comprise baseline data.
 2. A programmer according toclaim 1, wherein the analysis comprises one or more of: a monitor toaccumulate collected device measures and to derive derived devicemeasures for use in determining the wellness indicator relating tocardiovascular pressure; a patient well being analyzer to monitorpatient well being in conjunction with at least one of potassium level,sodium level, hormonal level, and blood pressure; and a programminginterface to apply programming data to effect therapy modificationselected from the group comprising device parameters, drug infusionparameters, and neural stimulation parameters.
 3. A programmer accordingto claim 1, further comprising: an evaluator to process physiometricdata conjunction with monitoring of the patient, wherein thephysiometric data is selected from the group comprising: analytic datarecorded, collected, and stored for cardiovascular pressure evaluation;alert data generated in response to significant events, wherein thealert data is selected from the group comprising absolute measures, longterm average measures, and short term average measures; and action dataexecuted in response to indications selected from the group comprisingthe significant events, ECG signals, activity level, temperature,pressure, and oxygen saturation.
 4. A programmer according to claim 1,further comprising: physiometric data comprising one or more of thecollected and derived device measures sensed through one or more ofcardiovascular pressure, potassium level, sodium level, hormonal level,central nervous system injury, and central nervous system blood flow. 5.A programmer according to claim 1, further comprising: programmingparameters, comprising at least one of: monitoring parameters to monitorthe patient while asleep; and exclusion parameters to excludephysiometric data comprising one or more of the collected and deriveddevice measures when the patient exhibits an increased respiratory ratedue to exercise or activity level.
 6. A programmer according to claim 1,further comprising: programmed trigger conditions with correspondingactions, wherein the actions are executed by the processor based uponthe direct and derived device measures to cause activation of one ormore of a therapy readout, alarm, or change in the raw physiometrymeasured, wherein the trigger conditions are selected from the groupcomprising absolute measures, pattern matching, absolute differencesbetween averaged measures, and comparisons of a current measure toanother current measure or a previous measure.
 7. An analysis system forgenerating baseline data for automated management of cardiovascularpressure, comprising: a structured database, comprising: collecteddevice measures to record raw physiometry for a patient, wherein thepatient is regularly monitored by an implantable medical device,beginning with an initial observation period; and derived devicemeasures to provide derivative physiometry determined at least in partfrom the collected device measures; an analyzer to determine a wellnessindicator through analysis of the collected and derived device measuresto diagnose a patient status indicative of at least one of a change anda status quo in cardiovascular pressure; and a processor to designatethe collected and derived device measures and the wellness indicatororiginating from the initial observation period as baseline data.
 8. Ananalysis system according to claim 7, wherein the structured databaseorganizes processed data to reflect one or more of: monitoring datacomprising collected and derived device measures and a wellnessindicator for cardiovascular pressure; patient well being data monitoredin conjunction with at least one of potassium level, sodium level,hormonal level, and blood pressure; and programming data to effecttherapy modification selected from the group comprising deviceparameters, drug infusion parameters, and neural stimulation parameters.9. An analysis system according to claim 7, wherein the processorprocesses physiometric data in conjunction with monitoring of thepatient, comprising at least one of: database management comprisingphysiometric data recording, collection, and storage for cardiovascularpressure evaluation; alert generation in response to significant events,wherein alert data is selected from the group comprising absolutemeasures, long term average measures, and short term average measures;and action execution in response to indications selected from the groupcomprising the significant events, ECG signals, activity level,temperature, pressure, and oxygen saturation.
 10. An analysis systemaccording to claim 7, further comprising: physiometric data comprisingone or more of the collected and derived device measures sensed throughone or more of cardiovascular pressure, potassium level, sodium level,hormonal level, central nervous system injury, and central nervoussystem blood flow.
 11. An analysis system according to claim 7, furthercomprising: a programming interface to generate programming parameters,comprising at least one of: monitoring parameters to monitor the patientwhile asleep; and exclusion parameters to exclude physiometric datacomprising one or more of the collected and derived device measures whenthe patient exhibits an increased respiratory rate due to exercise oractivity level.
 12. An analysis system according to claim 7, furthercomprising: defined trigger conditions with corresponding actions thatare executed based upon the direct and derived device measures to causeactivation of one or more of a therapy readout, alarm, or change in theraw physiometry measured, wherein the trigger conditions are selectedfrom the group comprising absolute measures, pattern matching, absolutedifferences between averaged measures, and comparisons of a currentmeasure to another current measure or a previous measure.
 13. A methodfor generating baseline data for automated management of cardiovascularpressure, comprising: using an implantable medical device to accumulatecollected device measures to record raw physiometry for a patient,wherein the patient is regularly monitored by the implantable medicaldevice, beginning with an initial observation period; generating deriveddevice measures to provide derivative physiometry determined at least inpart from the collected device measures; and determining a wellnessindicator by using a processor to analyze the collected and deriveddevice measures to diagnose a patient status indicative of at least oneof a change and a status quo in cardiovascular pressure, wherein thecollected and derived device measures and the wellness indicatororiginating from the initial observation period comprise baseline data.14. A method according to claim 13, further comprising: processing data,comprising one or more of: monitoring data comprising collected andderived device measures and a wellness indicator relating tocardiovascular pressure; monitoring patient well being in conjunctionwith at least one of potassium level, sodium level, hormonal level, andblood pressure; and forming programming data to effect therapymodification selected from the group comprising device parameters, druginfusion parameters, and neural stimulation parameters.
 15. A methodaccording to claim 13, further comprising: processing physiometric datain conjunction with monitoring of the patient, comprising at least oneof: recording, collecting, and storing data for cardiovascular pressureevaluation; generating alert data in response to significant events,wherein the alert data is selected from the group comprising absolutemeasures, long term average measures, and short term average measures;and executing actions in response to indications selected from the groupcomprising the significant events, ECG signals, activity level,temperature, pressure, and oxygen saturation.
 16. A method according toclaim 13, wherein physiometric data comprising one or more of thecollected and derived device measures is sensed through one or more ofcardiovascular pressure, potassium level, sodium level, hormonal level,central nervous system injury, and central nervous system blood flow.17. A method according to claim 13, further comprising: generatingprogramming parameters, comprising at least one of: defining monitoringparameters to monitor the patient while asleep; and defining exclusionparameters to exclude physiometric data comprising one or more of thecollected and derived device measures when the patient exhibits anincreased respiratory rate due to exercise or activity level.
 18. Amethod according to claim 13, further comprising: executing triggerconditions with corresponding actions based upon the direct and deriveddevice measures to cause activation of one or more of a therapy readout,alarm, or change in the raw physiometry measured, wherein the triggerconditions are selected from the group comprising absolute measures,pattern matching, absolute differences between averaged measures, andcomparisons of a current measure to another current measure or aprevious measure.